Algorithm 1: CNN algorithm for PV fault detection.

Input: [X,y]; label raw data. Preprocessing: normalization and resampling Convolution layer: CL←[X,y] raw data sent to the CNN for feature extraction F: feature vector (feature map) extracted from convolution layer Pooling layer: MaxPool←F;[X,y] downsampling feature map with MaxPool $F_D$; downsampled feature vector or feature map Flatten layer:$F_L$←$F_D$; change dimension of $F_D$ $F_L$: flatten feature map Fully connected layer:$F_C$←$F_L$; compute more advanced features and give probability values of each class P: probabilities of all the classes Output: classifies the test data